TIME SERIES ANALYSIS

Name: TIME SERIES ANALYSIS
Availability: OutOfStock
Rating: 3.8 (60 reviews)

POLISCI 917

과목 설명

This course introduces students to time series methods and applications, including ARMA models, error corrections models and reduced form specifications. Course also discusses co-integration and fractional integration.

선수과목

POLISCI 812 and POLISCI 813

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

미보고

평점

2.69

-12.13% 과거 데이터 대비

수료율

68.75%

-15.82% 과거 데이터 대비

A 비율

56.25%

-11.18% 과거 데이터 대비

학급 규모

33.33% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

REGRESSION AND TIME SERIES FOR ACTUARIES

ACTSCI 654

Foundation of multiple regression and time series analysis with focus on business. Introduction to skills needed to become critical consumers of reports that are based on regression and time series analysis.

APPLIED TIME SERIES ANALYSIS, FORECASTING AND CONTROL I

STAT 701

Theory and application of discrete time series models illustrated with forecasting problems. Principles of iterative model building. Representation of dynamic relations by difference equations. Autoregressive integrated Moving Average models. Identification, fitting, diagnostic checking of models. Seasonal model application to forecasting in business, economics, ecology, and engineering used at each stage, which the student analyzes using computer programs which have been specially written and extensively tested.

TOPICS IN APPLIED ECONOMETRICS

ECON 718

Applied time series methods.

ECONOMIC FORECASTING

ECON 460

Introduction to econometric time series analysis, forecasting methods, and forecast evaluation. Covers theoretical, methodological, and applied topics, and much of the work will be hands-on data analysis.

INTRODUCTION TO TIME SERIES

STAT 349

Autocorrelation; stationarity and non-stationarity; heteroscedasticity; dynamic models; auto-regressive and moving average models; identification and fitting; forecasting; seasonal adjustment; applications for financial time series, social sciences and environmental studies.